Nan Li
0000-0001-6800-7389
University of Nottingham
26 papers found
Refreshing results…
Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging
Optimising Automatic Morphological Classification of Galaxies with Machine Learning and Deep Learning using Dark Energy Survey Imaging
CosmoDC2: A Synthetic Sky Catalog for Dark Energy Science with LSST
The use of convolutional neural networks for modelling large optically-selected strong galaxy-lens samples
The Importance of Secondary Halos for Strong Lensing in Massive Galaxy Clusters across Redshift
Automated Lensing Learner: Automated Strong Lensing Identification with a Computer Vision Technique
The strong gravitational lens finding challenge
The South Pole Telescope Strong Lensing Cluster Sample
Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images
Identifying Strong Lenses with Unsupervised Machine Learning using Convolutional Autoencoder
Galaxy–Galaxy Weak-lensing Measurements from SDSS. II. Host Halo Properties of Galaxy Groups
The Strong Gravitational Lens Finding Challenge
Calibrating First-Order Strong Lensing Mass Estimates in Clusters of Galaxies
A Robust Mass Estimator for Dark Matter Subhalo Perturbations in Strong Gravitational Lenses
CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding
Galaxy–Galaxy Weak-lensing Measurements from SDSS. I. Image Processing and Lensing Signals
The Gini Coefficient as a Morphological Measurement of Strongly Lensed Galaxies in the Image Plane
Parallel DTFE Surface Density Field Reconstruction
Pics: Simulations of Strong Gravitational Lensing in Galaxy Clusters
The Gini Coefficient as a Tool for Image Family Idenitification in Strong Lensing Systems With Multiple Images
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